In [118]:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

1. line plot¶

In [6]:
var =[1,2,3,4,5,6,7]
var_1 =[2,3,4,1,5,6,7]

x_1 = pd.DataFrame({"var":var,"var_1":var_1})
sns.lineplot(x="var",y="var_1",data=x_1)
plt.show()
In [8]:
y_1 = sns.load_dataset("penguins")
y_1
Out[8]:
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex
0 Adelie Torgersen 39.1 18.7 181.0 3750.0 Male
1 Adelie Torgersen 39.5 17.4 186.0 3800.0 Female
2 Adelie Torgersen 40.3 18.0 195.0 3250.0 Female
3 Adelie Torgersen NaN NaN NaN NaN NaN
4 Adelie Torgersen 36.7 19.3 193.0 3450.0 Female
... ... ... ... ... ... ... ...
339 Gentoo Biscoe NaN NaN NaN NaN NaN
340 Gentoo Biscoe 46.8 14.3 215.0 4850.0 Female
341 Gentoo Biscoe 50.4 15.7 222.0 5750.0 Male
342 Gentoo Biscoe 45.2 14.8 212.0 5200.0 Female
343 Gentoo Biscoe 49.9 16.1 213.0 5400.0 Male

344 rows × 7 columns

In [9]:
sns.lineplot(x="bill_length_mm",y="flipper_length_mm",data=y_1)
plt.show()

hue¶

In [12]:
sns.lineplot(x="bill_length_mm",y="bill_depth_mm",data=y_1,hue="sex")
Out[12]:
<Axes: xlabel='bill_length_mm', ylabel='bill_depth_mm'>

size,style,palette,marker,dash¶

In [23]:
sns.lineplot(x="bill_length_mm",y="bill_depth_mm",data=y_1,hue="sex",size=20,style="sex",palette="Accent_r",markers=["o",">"],)
plt.show()

head¶

In [20]:
y_1 = sns.load_dataset("penguins").head(20)
y_1
Out[20]:
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex
0 Adelie Torgersen 39.1 18.7 181.0 3750.0 Male
1 Adelie Torgersen 39.5 17.4 186.0 3800.0 Female
2 Adelie Torgersen 40.3 18.0 195.0 3250.0 Female
3 Adelie Torgersen NaN NaN NaN NaN NaN
4 Adelie Torgersen 36.7 19.3 193.0 3450.0 Female
5 Adelie Torgersen 39.3 20.6 190.0 3650.0 Male
6 Adelie Torgersen 38.9 17.8 181.0 3625.0 Female
7 Adelie Torgersen 39.2 19.6 195.0 4675.0 Male
8 Adelie Torgersen 34.1 18.1 193.0 3475.0 NaN
9 Adelie Torgersen 42.0 20.2 190.0 4250.0 NaN
10 Adelie Torgersen 37.8 17.1 186.0 3300.0 NaN
11 Adelie Torgersen 37.8 17.3 180.0 3700.0 NaN
12 Adelie Torgersen 41.1 17.6 182.0 3200.0 Female
13 Adelie Torgersen 38.6 21.2 191.0 3800.0 Male
14 Adelie Torgersen 34.6 21.1 198.0 4400.0 Male
15 Adelie Torgersen 36.6 17.8 185.0 3700.0 Female
16 Adelie Torgersen 38.7 19.0 195.0 3450.0 Female
17 Adelie Torgersen 42.5 20.7 197.0 4500.0 Male
18 Adelie Torgersen 34.4 18.4 184.0 3325.0 Female
19 Adelie Torgersen 46.0 21.5 194.0 4200.0 Male
In [24]:
sns.lineplot(x="bill_length_mm",y="bill_depth_mm",data=y_1,hue="sex",size=20,style="sex",palette="Accent_r",markers=["o",">"],
            dashes=False)
plt.show()
In [25]:
sns.lineplot(x="bill_length_mm",y="bill_depth_mm",data=y_1,hue="sex",size=20,style="sex",palette="Accent_r",markers=["o",">"],
            dashes=False,legend="full")
plt.grid()
plt.title("Nnn")
plt.show()

2. histogram¶

In [26]:
y_1
Out[26]:
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex
0 Adelie Torgersen 39.1 18.7 181.0 3750.0 Male
1 Adelie Torgersen 39.5 17.4 186.0 3800.0 Female
2 Adelie Torgersen 40.3 18.0 195.0 3250.0 Female
3 Adelie Torgersen NaN NaN NaN NaN NaN
4 Adelie Torgersen 36.7 19.3 193.0 3450.0 Female
5 Adelie Torgersen 39.3 20.6 190.0 3650.0 Male
6 Adelie Torgersen 38.9 17.8 181.0 3625.0 Female
7 Adelie Torgersen 39.2 19.6 195.0 4675.0 Male
8 Adelie Torgersen 34.1 18.1 193.0 3475.0 NaN
9 Adelie Torgersen 42.0 20.2 190.0 4250.0 NaN
10 Adelie Torgersen 37.8 17.1 186.0 3300.0 NaN
11 Adelie Torgersen 37.8 17.3 180.0 3700.0 NaN
12 Adelie Torgersen 41.1 17.6 182.0 3200.0 Female
13 Adelie Torgersen 38.6 21.2 191.0 3800.0 Male
14 Adelie Torgersen 34.6 21.1 198.0 4400.0 Male
15 Adelie Torgersen 36.6 17.8 185.0 3700.0 Female
16 Adelie Torgersen 38.7 19.0 195.0 3450.0 Female
17 Adelie Torgersen 42.5 20.7 197.0 4500.0 Male
18 Adelie Torgersen 34.4 18.4 184.0 3325.0 Female
19 Adelie Torgersen 46.0 21.5 194.0 4200.0 Male
In [33]:
sns.displot(y_1["flipper_length_mm"])
plt.show()

bins¶

In [38]:
sns.displot(y_1["flipper_length_mm"],bins=[170,180,190,200,210,220,230,240])
plt.show()

kde¶

In [42]:
sns.displot(y_1["flipper_length_mm"],kde=True)
plt.show()
In [43]:
y_1.head(20)
Out[43]:
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex
0 Adelie Torgersen 39.1 18.7 181.0 3750.0 Male
1 Adelie Torgersen 39.5 17.4 186.0 3800.0 Female
2 Adelie Torgersen 40.3 18.0 195.0 3250.0 Female
3 Adelie Torgersen NaN NaN NaN NaN NaN
4 Adelie Torgersen 36.7 19.3 193.0 3450.0 Female
5 Adelie Torgersen 39.3 20.6 190.0 3650.0 Male
6 Adelie Torgersen 38.9 17.8 181.0 3625.0 Female
7 Adelie Torgersen 39.2 19.6 195.0 4675.0 Male
8 Adelie Torgersen 34.1 18.1 193.0 3475.0 NaN
9 Adelie Torgersen 42.0 20.2 190.0 4250.0 NaN
10 Adelie Torgersen 37.8 17.1 186.0 3300.0 NaN
11 Adelie Torgersen 37.8 17.3 180.0 3700.0 NaN
12 Adelie Torgersen 41.1 17.6 182.0 3200.0 Female
13 Adelie Torgersen 38.6 21.2 191.0 3800.0 Male
14 Adelie Torgersen 34.6 21.1 198.0 4400.0 Male
15 Adelie Torgersen 36.6 17.8 185.0 3700.0 Female
16 Adelie Torgersen 38.7 19.0 195.0 3450.0 Female
17 Adelie Torgersen 42.5 20.7 197.0 4500.0 Male
18 Adelie Torgersen 34.4 18.4 184.0 3325.0 Female
19 Adelie Torgersen 46.0 21.5 194.0 4200.0 Male
In [44]:
sns.displot(y_1["flipper_length_mm"],kde=True)
plt.show()

rug¶

In [46]:
sns.displot(y_1["flipper_length_mm"],kde=True,rug=True,color="m")
plt.show()

log_scale¶

In [47]:
sns.displot(y_1["flipper_length_mm"],kde=True,rug=True,color="m",log_scale=True)
plt.show()

3. bar plot¶

In [54]:
y_1 = sns.load_dataset("penguins")
y_1
Out[54]:
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex
0 Adelie Torgersen 39.1 18.7 181.0 3750.0 Male
1 Adelie Torgersen 39.5 17.4 186.0 3800.0 Female
2 Adelie Torgersen 40.3 18.0 195.0 3250.0 Female
3 Adelie Torgersen NaN NaN NaN NaN NaN
4 Adelie Torgersen 36.7 19.3 193.0 3450.0 Female
... ... ... ... ... ... ... ...
339 Gentoo Biscoe NaN NaN NaN NaN NaN
340 Gentoo Biscoe 46.8 14.3 215.0 4850.0 Female
341 Gentoo Biscoe 50.4 15.7 222.0 5750.0 Male
342 Gentoo Biscoe 45.2 14.8 212.0 5200.0 Female
343 Gentoo Biscoe 49.9 16.1 213.0 5400.0 Male

344 rows × 7 columns

In [59]:
sns.barplot(x=y_1.island,y=y_1.bill_length_mm)
plt.show()
In [63]:
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex")
plt.show()

order¶

In [65]:
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1)
plt.show()
In [66]:
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"])
plt.show()

ci¶

In [70]:
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3)
plt.show()

C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\4267160353.py:2: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.

  sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3)

horzontal(orient)¶

In [76]:
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
            orient="v")
plt.show()

C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\2636899640.py:2: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.

  sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,

color¶

In [84]:
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,color="r")
plt.show()

palette¶

In [85]:
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
            orient="v",palette="Accent")
plt.show()

C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\2793013636.py:2: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.

  sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
In [89]:
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
            orient="v",palette="Accent",saturation=0)
plt.show()

C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\3405270278.py:2: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.

  sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
In [91]:
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
            orient="v",palette="Accent",errcolor="m",errwidth="5",errorbar="10")
plt.show()

C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\4156774541.py:2: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.

  sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,

capsize¶

In [95]:
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
            orient="v",palette="Accent",errcolor="m",errwidth="5",errorbar="10",capsize=.2)
plt.show()

C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\906675546.py:2: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.

  sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,

alpha¶

In [99]:
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
            orient="v",palette="Accent",errcolor="m",errwidth="5",errorbar="10",alpha=.5)
plt.show()

C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\1870751630.py:2: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.

  sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,

4. scatter plot¶

In [101]:
y_1
Out[101]:
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex
0 Adelie Torgersen 39.1 18.7 181.0 3750.0 Male
1 Adelie Torgersen 39.5 17.4 186.0 3800.0 Female
2 Adelie Torgersen 40.3 18.0 195.0 3250.0 Female
3 Adelie Torgersen NaN NaN NaN NaN NaN
4 Adelie Torgersen 36.7 19.3 193.0 3450.0 Female
... ... ... ... ... ... ... ...
339 Gentoo Biscoe NaN NaN NaN NaN NaN
340 Gentoo Biscoe 46.8 14.3 215.0 4850.0 Female
341 Gentoo Biscoe 50.4 15.7 222.0 5750.0 Male
342 Gentoo Biscoe 45.2 14.8 212.0 5200.0 Female
343 Gentoo Biscoe 49.9 16.1 213.0 5400.0 Male

344 rows × 7 columns

In [103]:
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1)
           
plt.show()

hue¶

In [104]:
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1,hue="sex")
           
plt.show()
In [105]:
y_1.head(20)
Out[105]:
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex
0 Adelie Torgersen 39.1 18.7 181.0 3750.0 Male
1 Adelie Torgersen 39.5 17.4 186.0 3800.0 Female
2 Adelie Torgersen 40.3 18.0 195.0 3250.0 Female
3 Adelie Torgersen NaN NaN NaN NaN NaN
4 Adelie Torgersen 36.7 19.3 193.0 3450.0 Female
5 Adelie Torgersen 39.3 20.6 190.0 3650.0 Male
6 Adelie Torgersen 38.9 17.8 181.0 3625.0 Female
7 Adelie Torgersen 39.2 19.6 195.0 4675.0 Male
8 Adelie Torgersen 34.1 18.1 193.0 3475.0 NaN
9 Adelie Torgersen 42.0 20.2 190.0 4250.0 NaN
10 Adelie Torgersen 37.8 17.1 186.0 3300.0 NaN
11 Adelie Torgersen 37.8 17.3 180.0 3700.0 NaN
12 Adelie Torgersen 41.1 17.6 182.0 3200.0 Female
13 Adelie Torgersen 38.6 21.2 191.0 3800.0 Male
14 Adelie Torgersen 34.6 21.1 198.0 4400.0 Male
15 Adelie Torgersen 36.6 17.8 185.0 3700.0 Female
16 Adelie Torgersen 38.7 19.0 195.0 3450.0 Female
17 Adelie Torgersen 42.5 20.7 197.0 4500.0 Male
18 Adelie Torgersen 34.4 18.4 184.0 3325.0 Female
19 Adelie Torgersen 46.0 21.5 194.0 4200.0 Male
In [111]:
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1,hue="sex",style="sex",size="sex",sizes=(120,40))
y_1
plt.show()

color / palatte¶

In [112]:
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1,hue="sex",style="sex",size="sex",sizes=(120,40)
                ,palette="Accent")
y_1
plt.show()

alpha¶

In [113]:
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1,hue="sex",style="sex",size="sex",sizes=(120,40),
                palette="Accent",alpha=.5)
y_1
plt.show()
In [119]:
m = {"Male":"*","Female":"o"}
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1,hue="sex",sizes=(120,40),
               markers=m)

plt.show()

5 Heatmap¶

In [10]:
data = sns.load_dataset("anagrams").head(10)
data
Out[10]:
subidr attnr num1 num2 num3
0 1 divided 2 4.0 7
1 2 divided 3 4.0 5
2 3 divided 3 5.0 6
3 4 divided 5 7.0 5
4 5 divided 4 5.0 8
5 6 divided 5 5.0 6
6 7 divided 5 4.5 6
7 8 divided 5 7.0 8
8 9 divided 2 3.0 7
9 10 divided 6 5.0 6
In [12]:
data = sns.load_dataset("anagrams")
x=data.drop(columns=["attnr"],axis=1).head(10)
x
Out[12]:
subidr num1 num2 num3
0 1 2 4.0 7
1 2 3 4.0 5
2 3 3 5.0 6
3 4 5 7.0 5
4 5 4 5.0 8
5 6 5 5.0 6
6 7 5 4.5 6
7 8 5 7.0 8
8 9 2 3.0 7
9 10 6 5.0 6
In [13]:
sns.heatmap(x)
plt.show()

min & max¶

In [14]:
sns.heatmap(x,vmin=0,vmax=12)
plt.show()

cmap¶

In [25]:
sns.heatmap(x,vmin=0,vmax=12,cmap="PuOr")
plt.show()

annot¶

In [26]:
sns.heatmap(x,vmin=0,vmax=12,cmap="PuOr",annot=True)
plt.show()
In [31]:
y ={"fontsize":12,"color":"g"}
sns.heatmap(x,vmin=0,vmax=12,cmap="PuOr",annot=True,annot_kws=y,linewidths=10,linecolor="g")
plt.show()

xticslabels & ytickslabel & cbar¶

In [32]:
y ={"fontsize":12,"color":"g"}
sns.heatmap(x,vmin=0,vmax=12,cmap="PuOr",annot=True,annot_kws=y,linewidths=10,linecolor="g",
           cbar=False,xticklabels=False,yticklabels=False)
plt.show()

xlabel , ylabel using set function¶

In [35]:
 y ={"fontsize":12,"color":"g"}
v =sns.heatmap(x,vmin=0,vmax=12,cmap="PuOr",annot=True,annot_kws=y,linewidths=10,linecolor="g",
           cbar=False,xticklabels=False,yticklabels=False)
v.set(xlabel="python",ylabel="NnN")
sns.set(font_scale=1.2)
plt.show()

6 Count plot¶

In [45]:
var = sns.load_dataset("tips")
var
Out[45]:
total_bill tip sex smoker day time size
0 16.99 1.01 Female No Sun Dinner 2
1 10.34 1.66 Male No Sun Dinner 3
2 21.01 3.50 Male No Sun Dinner 3
3 23.68 3.31 Male No Sun Dinner 2
4 24.59 3.61 Female No Sun Dinner 4
... ... ... ... ... ... ... ...
239 29.03 5.92 Male No Sat Dinner 3
240 27.18 2.00 Female Yes Sat Dinner 2
241 22.67 2.00 Male Yes Sat Dinner 2
242 17.82 1.75 Male No Sat Dinner 2
243 18.78 3.00 Female No Thur Dinner 2

244 rows × 7 columns

In [46]:
sns.countplot(x="sex",data=var,hue="sex")
plt.show()
In [47]:
sns.countplot(x="sex",data=var,hue="smoker")
plt.show()
In [48]:
sns.countplot(y="sex",data=var,hue="smoker")
plt.show()

Palette¶

In [50]:
sns.countplot(x="sex",data=var,hue="smoker",palette="bwr")
plt.show()

saturation¶

In [51]:
sns.countplot(x="sex",data=var,hue="smoker",palette="bwr",saturation=.6)
plt.show()

7 Violin plot¶

In [2]:
var = sns.load_dataset("tips")
var
Out[2]:
total_bill tip sex smoker day time size
0 16.99 1.01 Female No Sun Dinner 2
1 10.34 1.66 Male No Sun Dinner 3
2 21.01 3.50 Male No Sun Dinner 3
3 23.68 3.31 Male No Sun Dinner 2
4 24.59 3.61 Female No Sun Dinner 4
... ... ... ... ... ... ... ...
239 29.03 5.92 Male No Sat Dinner 3
240 27.18 2.00 Female Yes Sat Dinner 2
241 22.67 2.00 Male Yes Sat Dinner 2
242 17.82 1.75 Male No Sat Dinner 2
243 18.78 3.00 Female No Thur Dinner 2

244 rows × 7 columns

In [3]:
sns.violinplot(x="day",y="total_bill",data=var)
plt.show()

hue¶

In [4]:
sns.violinplot(x="day",y="total_bill",data=var)
plt.show()

linewidth,palette(color)¶

In [11]:
sns.violinplot(x="day",y="total_bill",data=var,hue="time",linewidth=2,palette="Dark2_r")
plt.show()

order¶

In [13]:
sns.violinplot(x="time",y="total_bill",data=var,linewidth=2,palette="Dark2_r",order=["Dinner","Lunch"])
plt.show()
In [14]:
sns.violinplot(x="time",y="tip",data=var,linewidth=2,palette="Dark2_r",order=["Dinner","Lunch"])
plt.show()

saturation & color¶

In [24]:
sns.violinplot(x="day",y="total_bill",data=var,linewidth=2,saturation=.4,color="r")
plt.show()

split¶

In [27]:
sns.violinplot(x="day",y="total_bill",data=var,hue="sex",split=True)
plt.show()

scale¶

In [28]:
sns.violinplot(x="day",y="total_bill",data=var,hue="sex",split=True,scale="count")
plt.show()
In [29]:
sns.violinplot(x="day",y="total_bill",data=var,hue="sex",split=True,scale="area")
plt.show()
In [30]:
sns.violinplot(x="day",y="total_bill",data=var,hue="sex",split=True,scale="width")
plt.show()

horizontal¶

In [31]:
sns.violinplot(x="total_bill",y="day",data=var,hue="sex")
plt.show()

inner¶

In [35]:
sns.violinplot(x="time",y="total_bill",data=var,hue="sex",order=["Dinner","Lunch"],inner="quart")
plt.show()
In [36]:
sns.violinplot(x="time",y="total_bill",data=var,hue="sex",order=["Dinner","Lunch"],inner="point")
plt.show()
In [37]:
sns.violinplot(x="time",y="total_bill",data=var,hue="sex",order=["Dinner","Lunch"],inner="stick")
plt.show()
In [38]:
sns.violinplot(x="time",y="total_bill",data=var,hue="sex",order=["Dinner","Lunch"],inner="box")
plt.show()

single violin plot¶

In [39]:
sns.violinplot(x=var["total_bill"])
plt.show()
In [40]:
sns.violinplot(y=var["total_bill"])
plt.show()

8 pair plot¶

In [41]:
sns.pairplot(var)
plt.show()

hue¶

In [42]:
sns.pairplot(var,hue="sex")
plt.show()

vars¶

In [43]:
sns.pairplot(var,vars=["tip","total_bill"],hue="sex")
plt.show()
In [45]:
sns.pairplot(var,vars=["tip","total_bill"],hue="sex",hue_order=["Female","Male"])
plt.show()

color(palette)¶

In [46]:
sns.pairplot(var,vars=["tip","total_bill"],hue="sex",hue_order=["Female","Male"],palette="BuGn")
plt.show()

x axis & y axis¶

In [48]:
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],x_vars=["total_bill","tip"])
plt.show()
In [49]:
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],y_vars=["total_bill","tip"])
plt.show()

kind:(reg , scatter , kde , hist)¶

In [51]:
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],kind="reg")
plt.show()
In [52]:
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],kind="kde")
plt.show()
In [53]:
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],kind="hist")
plt.show()
In [54]:
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],kind="scatter")
plt.show()
In [55]:
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],kind="reg",diag_kind="kde")
plt.show()

markers¶

In [57]:
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],markers=["*","^"])
plt.show()

9 strip plot¶

In [59]:
var
Out[59]:
total_bill tip sex smoker day time size
0 16.99 1.01 Female No Sun Dinner 2
1 10.34 1.66 Male No Sun Dinner 3
2 21.01 3.50 Male No Sun Dinner 3
3 23.68 3.31 Male No Sun Dinner 2
4 24.59 3.61 Female No Sun Dinner 4
... ... ... ... ... ... ... ...
239 29.03 5.92 Male No Sat Dinner 3
240 27.18 2.00 Female Yes Sat Dinner 2
241 22.67 2.00 Male Yes Sat Dinner 2
242 17.82 1.75 Male No Sat Dinner 2
243 18.78 3.00 Female No Thur Dinner 2

244 rows × 7 columns

In [60]:
sns.stripplot(x="day",y="total_bill",data=var)
plt.show()
In [63]:
sns.stripplot(x="day",y="total_bill",data=var,hue="sex")
plt.show()
In [79]:
sns.stripplot(x="day",y="total_bill",data=var,hue="sex",palette="rocket_r",linewidth=1.2,edgecolor="m",jitter=.4,size=4)
plt.show()

marker¶

In [84]:
m ={"Male":"*","Female":"o"}
sns.stripplot(x="day",y="total_bill",data=var,hue="sex",marker="*")
plt.show()

alpha¶

In [88]:
sns.stripplot(x="day",y="total_bill",data=var,hue="sex",palette="rocket_r",linewidth=1.2,edgecolor="m",jitter=.4,size=4,
             alpha=.6)
plt.show()

single value strp plot¶

In [89]:
sns.stripplot(x=var["total_bill"],data=var,hue="sex",marker="*")
plt.show()
In [90]:
sns.stripplot(y=var["total_bill"],data=var,hue="sex",marker="*")
plt.show()

10 Box plot¶

In [91]:
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var)
plt.show()

hue¶

In [92]:
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,hue="time")
plt.show()
In [93]:
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,hue="sex")
plt.show()
In [94]:
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,hue="sex",color="m")
plt.show()

order, showmeans,meansprop,lonewidh,palette¶

In [97]:
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,hue="sex",color="m",order=["Sun","Sat","Fri","Thur"],showmeans=True)
plt.show()
In [98]:
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,color="r",order=["Sun","Sat","Fri","Thur"],showmeans=True)
plt.show()
In [100]:
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,color="g",order=["Sun","Sat","Fri","Thur"],showmeans=True,
            meanprops={"marker":"+","markeredgecolor":"r"})
plt.show()
In [103]:
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,color="g",order=["Sun","Sat","Fri","Thur"],showmeans=True,
            meanprops={"marker":"+","markeredgecolor":"r"},linewidth=.3,palette="plasma")
plt.show()

horizontal & verticle box plot¶

In [109]:
sns.set(style="whitegrid")
sns.boxplot(x="total_bill",y="day",data=var,color="g",order=["Sun","Sat","Fri","Thur"],showmeans=True,
            meanprops={"marker":"+","markeredgecolor":"r"},linewidth=.3,palette="plasma")
plt.show()
In [107]:
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,color="g",order=["Sun","Sat","Fri","Thur"],showmeans=True,
            meanprops={"marker":"+","markeredgecolor":"r"},linewidth=.3,palette="plasma",orient="v")
plt.show()

single data set box plot¶

In [111]:
sns.set(style="whitegrid")
sns.boxplot(x=var["total_bill"])
plt.show()
In [112]:
sns.set(style="whitegrid")
sns.boxplot(y=var["total_bill"])
plt.show()

11 cator plot OR Factor plot¶

In [114]:
var
Out[114]:
total_bill tip sex smoker day time size
0 16.99 1.01 Female No Sun Dinner 2
1 10.34 1.66 Male No Sun Dinner 3
2 21.01 3.50 Male No Sun Dinner 3
3 23.68 3.31 Male No Sun Dinner 2
4 24.59 3.61 Female No Sun Dinner 4
... ... ... ... ... ... ... ...
239 29.03 5.92 Male No Sat Dinner 3
240 27.18 2.00 Female Yes Sat Dinner 2
241 22.67 2.00 Male Yes Sat Dinner 2
242 17.82 1.75 Male No Sat Dinner 2
243 18.78 3.00 Female No Thur Dinner 2

244 rows × 7 columns

hue,kind¶

In [123]:
sns.catplot(x="size",y="tip",data=var,hue="sex",kind="bar")
plt.show()
In [124]:
sns.catplot(x="size",y="tip",data=var,hue="sex",kind="box")
plt.show()
In [126]:
sns.catplot(x="size",y="tip",data=var,hue="sex",kind="strip")
plt.show()
In [132]:
sns.catplot(x="tip",y="size",data=var,hue="sex",palette="Oranges")
plt.show()
In [140]:
sns.catplot(x="day",y="size",data=var,hue="sex",kind="point",palette="Accent")
plt.show()
In [141]:
sns.catplot(x="day",y="size",data=var,hue="sex",kind="boxen",palette="Accent")
plt.show()

12 Styling plot¶

1. seaborn figure styles¶

In [142]:
var
Out[142]:
total_bill tip sex smoker day time size
0 16.99 1.01 Female No Sun Dinner 2
1 10.34 1.66 Male No Sun Dinner 3
2 21.01 3.50 Male No Sun Dinner 3
3 23.68 3.31 Male No Sun Dinner 2
4 24.59 3.61 Female No Sun Dinner 4
... ... ... ... ... ... ... ...
239 29.03 5.92 Male No Sat Dinner 3
240 27.18 2.00 Female Yes Sat Dinner 2
241 22.67 2.00 Male Yes Sat Dinner 2
242 17.82 1.75 Male No Sat Dinner 2
243 18.78 3.00 Female No Thur Dinner 2

244 rows × 7 columns

In [143]:
sns.set_style("white")  
sns.barplot(x="day",y="total_bill",data=var)
plt.show()
In [144]:
sns.set_style("dark")  
sns.barplot(x="day",y="total_bill",data=var)
plt.show()
In [145]:
sns.set_style("whitegrid")  
sns.barplot(x="day",y="total_bill",data=var)
plt.show()
In [146]:
sns.set_style("darkgrid")  
sns.barplot(x="day",y="total_bill",data=var)
plt.show()

2.Removing axes spines¶

In [148]:
sns.set_style("white")  
sns.barplot(x="day",y="total_bill",data=var)
sns.despine()
plt.show()

3. scale & context¶

In [150]:
sns.set_style("white")  
plt.figure(figsize=(3,2))
sns.barplot(x="day",y="total_bill",data=var)
sns.despine()
plt.show()
In [154]:
sns.set_style("white")  
# plt.figure(figsize=(3,2))
sns.set_context("poster",font_scale=1)
sns.barplot(x="day",y="total_bill",data=var)
# sns.despine()
plt.show()
In [156]:
sns.set_style("white")  
# plt.figure(figsize=(3,2))
sns.set_context("paper",font_scale=1)
sns.barplot(x="day",y="total_bill",data=var,palette="cool")
# sns.despine()
plt.show()

13. FacetGrid (multiple plots)¶

In [157]:
var
Out[157]:
total_bill tip sex smoker day time size
0 16.99 1.01 Female No Sun Dinner 2
1 10.34 1.66 Male No Sun Dinner 3
2 21.01 3.50 Male No Sun Dinner 3
3 23.68 3.31 Male No Sun Dinner 2
4 24.59 3.61 Female No Sun Dinner 4
... ... ... ... ... ... ... ...
239 29.03 5.92 Male No Sat Dinner 3
240 27.18 2.00 Female Yes Sat Dinner 2
241 22.67 2.00 Male Yes Sat Dinner 2
242 17.82 1.75 Male No Sat Dinner 2
243 18.78 3.00 Female No Thur Dinner 2

244 rows × 7 columns

In [162]:
fg=sns.FacetGrid(var,col="sex",hue="day")
fg.map(plt.scatter,"total_bill","tip").add_legend()
plt.show()
In [163]:
fg=sns.FacetGrid(var,col="day",hue="sex")
fg.map(plt.scatter,"total_bill","tip").add_legend()
plt.show()
In [170]:
fg=sns.FacetGrid(var,col="day",hue="sex")
fg.map(plt.bar,"total_bill","tip").add_legend()
plt.show()
In [172]:
fg=sns.FacetGrid(var,col="sex",hue="day",palette="cool")
fg.map(plt.bar,"total_bill","tip").add_legend()
plt.show()
In [175]:
fg=sns.FacetGrid(var,col="sex",hue="day",palette="summer")
fg.map(plt.bar,"total_bill","tip",edgecolor="r").add_legend()
plt.show()
In [ ]: